TSMCTS applies Sequential Monte Carlo in two stages for tree search, claiming better performance, favorable scaling with depth, lower variance, and reduced path degeneracy than SMC and modern MCTS baselines across discrete and continuous environments.
M is the number of actions over which the estimator maintains information (susceptible to path degeneracy)
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Twice Sequential Monte Carlo for Tree Search
TSMCTS applies Sequential Monte Carlo in two stages for tree search, claiming better performance, favorable scaling with depth, lower variance, and reduced path degeneracy than SMC and modern MCTS baselines across discrete and continuous environments.